Detecting the occluding contours of the uterus to automatise augmented laparoscopy: score, loss, dataset, evaluation and user study.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: The registration of a preoperative 3D model, reconstructed, for example, from MRI, to intraoperative laparoscopy 2D images, is the main challenge to achieve augmented reality in laparoscopy. The current systems have a major limitation: they require that the surgeon manually marks the occluding contours during surgery. This requires the surgeon to fully comprehend the non-trivial concept of occluding contours and surgeon time, directly impacting acceptance and usability. To overcome this limitation, we propose a complete framework for object-class occluding contour detection (OC2D), with application to uterus surgery.

Authors

  • Tom Francois
    EnCoV, Institut Pascal, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France.
  • Lilian Calvet
    EnCoV, Institut Pascal, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France.
  • Sabrina Madad Zadeh
    Department of Gynaecological Surgery, CHU Clermont-Ferrand, 1 Place Lucie et Raymond Aubrac, 63000, Clermont-Ferrand, France.
  • Damien Saboul
    Be-Studys, A Brand of Be-Ys Group, 123 Route de Meyrin, 1219 Châtelaine, Suisse, Vernier, Switzerland.
  • Simone Gasparini
    Université Clermont Auvergne, CHU Clermont-Ferrand, CNRS, SIGMA, Institut Pascal, Clermont-Ferrand, France.
  • Prasad Samarakoon
    Université Clermont Auvergne, CHU Clermont-Ferrand, CNRS, SIGMA, Institut Pascal, Clermont-Ferrand, France.
  • Nicolas Bourdel
    Department of Gynaecological Surgery, CHU Clermont-Ferrand, 1 Place Lucie et Raymond Aubrac, 63000, Clermont-Ferrand, France. nicolas.bourdel@gmail.com.
  • Adrien Bartoli
    EnCoV, Institut Pascal, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France.